Commodity Alpha Q4 2021 & beginning Q1 2022 commentary

* (net of trading costs, service fee and performance fee - considering a performance fee for investing since inception but, since your performance fee will depend on your point of entry, your net returns will vary too).

Market overview

Commodities ended the last quarter of 2021 lower, with the Bloomberg Commodity Index shedding -1.6%.

The final three months of the year were volatile, characterized by a slowdown of momentum across sectors as the broad rally in commodities appeared to decline. The uncertainty surrounding the severity of Omicron variant and potential for governments to impose further lockdowns globally caused markets to sell off violently in November.

Agriculture
Agriculture was the least profitable sector, with losses driven primarily by short positions in the Soy complex (Soybeans, Soybean meal and Soybean Oil) as well as Corn. The short positions performed well over November in the broad market sell-off, however took a downfall in December. . A worldwide shortage and record high prices of fertilizer are driving up food costs and creating a crisis. The production of fertilizer requires large amounts of gas, and the sharp rise in energy prices had driven up production costs. Additionally, the record-breaking draught in Chile had an impact on agriculture.

Energy
The strategy had long and short positions across the barrel, which resulted in average returns for Energy.
In Natural Gas, a shortage in supply had caused an explosion in prices which pulled energy markets higher, sending Europe and the UK into an energy crisis. A combination of factors led to this: a loss of supply from a fire in the main Norwegian gas plant, feed gas issues from Trinidad and Nigeria, less volume from Russia, aggressive restocking by Asia ahead of the winter season and very low wind speeds. 

Livestock
Livestock was the strategie’s strongest sector, with positive contribution every month of Q4 2021.Historically, hogs were at premium due to the African Swine Fever that decimated the hog herd in China. This led to China bidding up hogs from around the world briefly sending the price of pork to a premium over beef. Since then, the hog herd has replenished sending prices lower.

Metals
Metals was the next strongest sector for Q4 2021. The short positions in Palladium and Silver did well as markets trended lower from a high peak that was caused by the supply issues from years before. Gold was also a strong performer where the strategy made money on the long side, opportunistically buying when conditions were favorable.

85% of annual Palladium demand comes from the global automotive industry, which uses the metal in catalytic converters to control polluting emissions. In the short-term demand has been reduced as the global semi-conductor shortage has reduced car sales. Longer term, producers are concerned that demand is being destroyed by electric vehicles which don't require the catalytic converter.

Strategy performance (net of fees)

Since inception (May 2020): 114,39% ( net of trading costs, service fee and performance fee - considering a performance fee for investing since inception but, since your performance fee will depend on your point of entry, your net returns will vary too).

Beginning of 2022

January has been a challenging month for the strategy, where the short book took a downfall.  In January, the short exposures have not performed well since those commodities in fact rallied. At the same time, the long positions have not moved up as much (or in some cases fell). Short positions in Agriculture have been the toughest sector with losses driven by the soy-complex, followed by energy.

In energy, there is a shortage of oil inventory as OPEC+ have restricted output to drain the excess supplies that accumulated over the past two years. The fear that Omicron would bring further lockdowns has gone and markets expect demand for oil to continue to grow. Natural Gas prices have also rallied, pricing in a disruption to export, on a Ukraine-Russia war.

Volatility itself is neither good or bad; but a change of volatility characteristics of a commodity increases the difficulty of identifying price behavior, thus trade signal. It is also important to note that this model assigns a conviction to trade signals and only enters the highest conviction trades. Despite this, it is quite likely that any single commodity or position, at any given time, may not be correct and that is why the strategy always diversifies its exposure and positions are sized according to the volatility of the commodity. If there is a volatility breakout that is not modelled, then indeed that can create an unanticipated impact on returns. However, the likelihood that the model gets the signal wrong for every position at the same time, and that all volatility breakouts go against the portfolio, is highly improbable.